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- Title
Scoring model for discriminating gastric cancer risk in patients with negative serum pepsinogen and anti‐Helicobacter pylori antibody results.
- Authors
Cho, Jun‐Hyung; Jin, So‐Young; Park, Suyeon
- Abstract
Background: The ABC test measures serum pepsinogen and anti‐Helicobacter pylori IgG antibody levels to predict precancerous conditions in the stomach and gastric cancer. However, a limitation of this test is that the gastric cancer risk is not negligible in patients with a negative result. Methods: Based on their ABC results, 1157 patients were classified into Groups A (n = 392), B (n = 479), C (n = 247), and D (n = 39). In Group A, 24.2% of patients had atrophic gastritis and/or intestinal metaplasia and had thus been incorrectly assigned to Group A. Patients in Group A were then assigned to derivation (n = 236) and validation (n = 156) cohorts by 3:2 random sampling. Logistic regression analyses were performed to identify the factors discriminating between a correct (true) and incorrect (false) Group A classification. Results: A 4‐point discriminative model was constructed based on a high‐negative H. pylori IgG antibody titer and the patient's age (50–64 and ≥65 years). The areas under the receiver operating characteristic curve for the derivation and validation cohorts were 0.868 and 0.894, respectively. In the validation cohort, the addition of a discriminative model score ≥2 to the ABC method showed a similar accuracy for predicting gastric cancer risk compared with the ABC method alone (93.8% vs. 92.4%). Conclusion: The 4‐point discriminative model may help identify patients with a normal serological test who are nonetheless at risk of developing gastric cancer.
- Subjects
DISEASE risk factors; STOMACH cancer; PEPSINOGEN; CANCER patients; RECEIVER operating characteristic curves
- Publication
Journal of Gastroenterology & Hepatology, 2021, Vol 36, Issue 12, p3345
- ISSN
0815-9319
- Publication type
Article
- DOI
10.1111/jgh.15630